V7
AI data engine for labeling computer vision and medical imaging data.
About
V7 is a London-based AI data engine that accelerates training data creation for computer vision with automated image and video data pipelines, dataset versioning, and model-assisted labeling. Founded in 2018, it started in medical imaging with customers like GE Healthcare and Siemens, then expanded to general computer vision with 300+ clients.
The platform's Auto Annotate model automatically segments objects in images and video after about 100 human-guided examples, acting as a co-pilot for annotators. V7 has raised over $40M including a $33M Series A co-led by Radical Ventures and Temasek. Pricing starts around $199 per user per month, positioning it for funded teams rather than indie developers.
What it can do
- Auto-annotation agents
- Dataset versioning
- Medical imaging workflows
- Model training and deployment
- Quality review pipelines
Setup
Sign up on v7labs.com and start a labeling project.
Prerequisites
Image or video data to annotate; labeling team or solo workflow.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 84; Trending score 74/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.